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I OWA S TATE U NIVERSITY Department of Animal Science U.S. 2007 – 2012 Pork Industry Productivity Analysis C. E. Abell 1, C. Hostetler 2, and K. J. Stalder.

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Presentation on theme: "I OWA S TATE U NIVERSITY Department of Animal Science U.S. 2007 – 2012 Pork Industry Productivity Analysis C. E. Abell 1, C. Hostetler 2, and K. J. Stalder."— Presentation transcript:

1 I OWA S TATE U NIVERSITY Department of Animal Science U.S – 2012 Pork Industry Productivity Analysis C. E. Abell 1, C. Hostetler 2, and K. J. Stalder 1 1 Iowa State University, Ames, IA and National Pork Board, Des Moines, IA Swine Educators In-Service Atlanta, GA October 2 nd, 2013

2 I OWA S TATE U NIVERSITY Department of Animal Science Data Description Production data obtained from a large U.S. data record keeping organization Agreement with the National Pork Board to share limited information. Uses: 1. Quantify the annual production levels and variation associated for several key productivity indicators 2. Establish industry benchmarks for all swine production phases Breeding herd Nursery Wean – to – finish Conventional finishing

3 I OWA S TATE U NIVERSITY Department of Animal Science Data Description Production data obtained from a large U.S. data record keeping organization Agreement with the National Pork Board to share limited information. Uses: 3. Quantify seasonal affects associated with the key productivity indicators 4. Identify research opportunities that would improve the U.S. pork industry production efficiency

4 I OWA S TATE U NIVERSITY Department of Animal Science Data description Statistical process Industry Trends Raw means and standard deviations were used Seasonality evaluation Linear model was used Fixed effects Company Month Year Covariates – for nursery, grow-finish, and wean-to-finish Start age Start days Days in facility Covariates – Sow farm Weaning age

5 I OWA S TATE U NIVERSITY Department of Animal Science Data description cont Data (records) reported monthly for each production phase Nursery and finishing data – Monthly averages are based on animals exiting the facility that month Sow farm data – Monthly averages are based on litters weaned in that month

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7 I OWA S TATE U NIVERSITY Department of Animal Science Company / farm summary Increase in the number of companies and farms represented Tremendous increase in the data volume evaluated Results in improved information and interpretations that can be made Companies becoming much more data driven in their decision making process

8 I OWA S TATE U NIVERSITY Department of Animal Science Company / farm summary Grow-finish and wean-to-finish becoming farms becoming more like their sow farm counterparts Farm level decisions much more data driven Continue greater use of data when guiding company decision process regarding: Employee Financial Health Nutritional Genetic Some combination

9 I OWA S TATE U NIVERSITY Department of Animal Science Use the Data to Benchmark Compare with other businesses Within species Across species Compare herd performance Within company Within country Etc. Set goals for improving herd For a specific trait or several traits

10 I OWA S TATE U NIVERSITY Department of Animal Science Overall Averages

11 I OWA S TATE U NIVERSITY Department of Animal Science Key productivity indicators Sow farm KPIs Pigs/mated sow/ year Litters/mated sow/year Total born Still born and mummies Number born alive Number weaned Pre-weaning mortality % Weaning weight Weaning age

12 I OWA S TATE U NIVERSITY Department of Animal Science Key productivity indicators cont Nursery KPIs Nursery mortality % Nursery out weight Days in nursery Nursery feed conversion

13 I OWA S TATE U NIVERSITY Department of Animal Science Key productivity indicators cont Conventional finishers and wean-to-finish facilities KPIs Finisher (wean-to-finish) mortality % Finishing weight Days in finisher (wean-to-finish) Finisher feed conversion (wean-to-finish)

14 I OWA S TATE U NIVERSITY Department of Animal Science Key Productivity Indicator Averages Means and standard deviations across all farms and operations. Sow, nursery, wean-to-finish, and conventional grow- finish data Developed to examine yearly trends across the U.S. Swine industry. Operations can compare one or a number of KPIs to see if they are above or below average

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19 I OWA S TATE U NIVERSITY Department of Animal Science Overall data summary Finishing mortality has declined over time while market weight has continued to increase Improving mortality by 2% for a 1000 hd. finishing facility would be equivalent to adding $3,240 each barn turn assuming 270 lb. market hog and $60/cwt. Days in the finisher have remained relatively constant over time Average daily gain has increased slightly over time Feed conversion has improved slightly across both finishing facility types

20 I OWA S TATE U NIVERSITY Department of Animal Science Overall data summary cont Nursery performance has change little across the reporting time period Pigs/mated sow/ year has increased by almost 2 pigs from 2007 to Litters/mated sow/year has changed little during the time period Most of the improvement in PSY is a result of improved litter size Some of the PSY increase is greater stillborns and mummies Number weaned has increased by 0.8 pigs

21 I OWA S TATE U NIVERSITY Department of Animal Science Overall data summary cont Percent pre-weaning mortality has increased. Represents lost opportunity Easy to improve?? Weaning age has increased by 2 days from 2007 to Weaning weight has increased by 1 lb.

22 I OWA S TATE U NIVERSITY Department of Animal Science Plots of Averages

23 I OWA S TATE U NIVERSITY Department of Animal Science Description of figures Figures graphically depict the change for the top 25%, overall, and bottom 25% for each KPI for the 2007 to 2012 time period. Top 25% represented by red lines Overall average represented by black lines Bottom 25% represented by blue lines More easily view the rate of change for each KPI across the 2007 to 2012 time period

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32 I OWA S TATE U NIVERSITY Department of Animal Science Figure summary KPIs are changing at the same direction for all three groups Each group slope or rate of change may slightly differ Examples: 1. Litter size averages have increased at almost the same rate across the top 25%, overall average, and bottom 25%. Litter size limit not reached yet for any group

33 I OWA S TATE U NIVERSITY Department of Animal Science Seasonality Estimates

34 I OWA S TATE U NIVERSITY Department of Animal Science Seasonality graph description Least squares means were used to obtain the month estimates using the model previously described.

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37 I OWA S TATE U NIVERSITY Department of Animal Science Seasonality graph Graphs clearly show the months when decreased performance occurs for each KPI Decreased performance represents substantial productivity and economic losses for the US swine industry Identifying causes and methods to mitigate seasonality effects on the KPIs would have a large economic impact on the entire swine industry.

38 I OWA S TATE U NIVERSITY Department of Animal Science Summary The US swine industry has been successful at improving production efficiency Some traits (mortality) still represent future opportunities Increasing the pounds of pork produced in a given period of time and reduced finishing mortality has improved finishing throughput. Combining improved litter size and pounds of pork produced, the throughput of the US swine industry has increased as a whole.

39 I OWA S TATE U NIVERSITY Department of Animal Science Summary Key productivity indicator trait improvements may be the result of – Better genetics Improved health Superior management Other The results from this analysis can be used to determine when management practices need to be improved and/or maintained to ensure optimal performance level for each swine production phase.

40 I OWA S TATE U NIVERSITY Department of Animal Science Thank you for your time and attention ! Do you have any questions or comments?


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